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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING
Ricky Risnantoyo
STMIK Nusa Mandiri
Computer Science & IT Engineering

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Sentiment Analysis on Corona Virus Pandemic Using Machine Learning Algorithm Ricky Risnantoyo; Arifin Nugroho; Kresna Mandara
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 4, No 1 (2020): ---> EDISI JULI
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (341.262 KB) | DOI: 10.31289/jite.v4i1.3798

Abstract

Corona virus outbreaks that occur in almost all countries in the world have an impact not only in the health sector, but also in other sectors such as tourism, finance, transportation, etc. This raises a variety of sentiments from the public with the emergence of corona virus as a trending topic on Twitter social media. Twitter was chosen by the public because it can disseminate information in real time and can see market reactions quickly. This research uses "tweet" data or public tweet related to "Corona Virus" to see how the sentiment polarity arises. Text mining techniques and three machine learning classification algorithms are used, including Naive Bayes, Support Vector Machine (SVM), K-Nearest Neighbor (K-NN) to build a tweet classification model of sentiments whether they have positive, negative, or neutral polarity. The highest test results are generated by the Support Vector Machine (SVM) algorithm with an accuracy value of 76.21%, a precision value of 78.04%, and a recall value of 71.42%.Keywords: Machine Learning, Corona Virus, Twitter, Sentiment Analysis.
Co-Authors Arifin Nugroho Kresna Mandara